Geostatistical procedure for simulation of the 3D geometry of a natural fracture network conditioned by well bore observations

ABSTRACT

The disclosed embodiments include a method, apparatus, and computer program product for providing a geostatistical procedure for simulation of the 3D geometry of a natural fracture network conditioned by well bore observations.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a U.S. National Stage patent application ofInternational Patent Application No. PCT/US2013/057639, filed on Aug.30, 2013, the benefit of which is claimed and the disclosure of which isincorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to the field of computerizedreservoir modeling, and more particularly, to a system and methodconfigured to provide a geostatistical procedure for conditionalsimulation of the three-dimensional (3D) geometry of a natural fracturenetwork.

2. Discussion of the Related Art

In the oil and gas industry, reservoir modeling involves theconstruction of a computer model of a petroleum reservoir for thepurpose of improving estimation of reserves and making decisionsregarding the development of the field. For example, geological modelsmay be created to provide a static description of the reservoir prior toproduction. In contrast, reservoir simulation models may be created tosimulate the flow of fluids within the reservoir over its productionlifetime.

One challenge with reservoir modeling is the modeling of fractureswithin a reservoir, which requires a thorough understanding of flowcharacteristics, fracture network connectivity, and fracture-matrixinteraction. The correct modeling of the fractures is important as theproperties of fractures such as spatial distribution, aperture, length,height, conductivity, and connectivity significantly affect the flow ofreservoir fluids to the well bore.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative embodiments of the present invention are described indetail below with reference to the attached drawing figures, which areincorporated by reference herein and wherein:

FIGS. 1A-1C is a flowchart illustrating a method for conditionalsimulation of the 3D geometry of a natural fracture network inaccordance with the disclosed embodiments;

FIG. 2 is a diagram illustrating an algorithm for determining thesimulated fracture parameters from data analysis and geological analogsfor performing the conditional simulation of the 3D geometry of anatural fracture network in accordance with the disclosed embodiments;

FIG. 3 is a diagram illustrating an algorithm for determining the actualfracture parameters from image logs in well bores for performing theconditional simulation of the 3D geometry of a natural fracture networkin accordance with the disclosed embodiments; and

FIG. 4 is a block diagram illustrating one embodiment of a system forimplementing the disclosed embodiments.

DETAILED DESCRIPTION

The disclosed embodiments and advantages thereof are best understood byreferring to FIGS. 1-4 of the drawings, like numerals being used forlike and corresponding parts of the various drawings. Other features andadvantages of the disclosed embodiments will be or will become apparentto one of ordinary skill in the art upon examination of the followingfigures and detailed description. It is intended that all suchadditional features and advantages be included within the scope of thedisclosed embodiments. Further, the illustrated figures are onlyexemplary and are not intended to assert or imply any limitation withregard to the environment, architecture, design, or process in whichdifferent embodiments may be implemented.

FIGS. 1A-1C is a flowchart illustrating a method 100 for providingconditional simulation of the 3D geometry of a natural fracture networkin accordance with the disclosed embodiments. The method 100 begins atstep 102 by setting simulated fracture parameters determined from dataanalysis and geological analogs. For example, FIG. 2 illustrates analgorithm 200 for determining the simulated fracture parameters fromdata analysis and geological analogs for performing the conditionalsimulation of the 3D geometry of a natural fracture network inaccordance with the disclosed embodiments. As illustrated in FIG. 2, inone embodiment, the algorithm 200 for setting the simulated fractureparameters includes determining the minimum size of the fractures to besimulated (M) and also determining the number of fracture sets (NS).

For each of the fracture set (i), the algorithm 200 determines thecumulative frequency distribution of the strike length (l) for fracturesin the set (f_(1,i)). In addition, the algorithm 200 determines theprobability distribution of the ratio of strike length to dip length (r)for fractures in the set (f_(r,i)). The algorithm 200 also determinesthe probability distribution of the strike angle (θ) for fractures inthe set (f_(θ,i)) and the probability distribution of the dip angle (δ)for fractures in the set (f_(δ,i)). Additionally, for each of thefracture set (i), the algorithm 200 determines the degree of clusteringof the fractures for fractures in the set (C_(i)) the degree ofsmoothness of the fracture surfaces for fractures in the set (S_(i)). Inone embodiment, the degree of clustering of the fractures is assigned avalue ranging from 0 to 1, wherein 1 indicates the highest degree ofclustering of the fractures within the set. Similarly, in oneembodiment, the degree of smoothness of the fracture surfaces may beassigned a value ranging from 0 to 1, wherein 1 indicates the highestdegree of smoothness for the fracture surfaces within the set.

In addition, for each pair of fracture sets (i, j), the algorithm 200determines the probability that a fracture from set i truncates againsta fracture from set j (Prob {T_(ij)}). Alternatively, in certainembodiments (not depicted), the algorithm 200 may determine acorrelation coefficient r_(s) between a gridded secondary attribute andlocal fracture density.

Referring back to FIG. 1, following step 102, the method 100 at step 104determines actual fracture parameters from the image logs in wellbores.For instance, as illustrated in FIG. 3, in one embodiment, the method100 may execute an algorithm 300 for determining the actual fractureparameters. The algorithm 300 may take as input one or more image logstaken from one or more wellbores. From the image logs, the algorithm 300determines the number of observed fractures associated with the one ormore wellbores. For each observed fracture, the algorithm determines thelocation coordinates (x_(i), y_(i), z_(i)) where the fracture intersectsthe wellbore and also determines the strike length (θ_(i)) and diplength (δ_(i)) of the fracture at the intersection of the fracture andthe wellbore. Additionally, the algorithm 300 includes instructions fordetermining the number of imaged intervals over which the image logprovides data. For each image interval, the algorithm 300 determines thecoordinates of the endpoints (x_(1,i), y_(1,i), z_(1,i)) and (x_(2,i),y_(2,i), z_(2,i)) of the imaged intervals.

Once all the parameters are determined, the method 100 determines thelocations of seed points for fractures at step 106. For example, in oneembodiment, the method begins with the locations of observed fracturesand adds probabilistically selected locations for additional unobservedfractures to reach the target frequency of F_(L,i)(M) in each fractureset. In one embodiment, the selection of locations is controlled by theparameter C_(i) (the degree of clustering of the fractures within thefracture set). In certain embodiments, the selection of locations mayalso be controlled by a grid of secondary data, if provided.

At step 108, the method 100 assigns to each seed point a target strikelength (SL) and target dip length (DL). In one embodiment, the method100 assigns the target strike length and target dip length by drawingrandom values from the cumulative frequency distribution of the strikelength (l) for fractures in the set (F_(1,i)) and from the probabilitydistribution of the ratio of strike length to dip length (r) forfractures in the set (f_(r,i)). The method 100 at step 110 assigns toeach seed point an initial strike (θ) and dip (δ), using knownorientations at observed locations, and drawing randomly from theprobability distribution of the strike angle for fractures in the set(f_(θ)) and the probability distribution of the dip angle for fracturesin the set (f_(δ)).

At step 112, the method 100 determines whether any unobserved fracturesinconsistently intersect any imaged intervals. If the method 100determines that an unobserved fracture inconsistently intersects animaged interval, the method 100 at step 114 alters the assigned valuesof SL, DL, θ and δ. In one embodiment, each of the values may bereplaced with a different randomly drawn value from the respectiveprobability distribution. Alternatively, in some embodiments, the method100 may determine to alter only certain values. For example, in oneembodiment, the method 100 may determine that only the initial dip (δ)is altered. Still, in some embodiments, the method 100 may execute analgorithm to determine an adjustment to one or more of the values asopposed to replacing the one or more values with a randomly selectedvalue. The method 100 then repeats step 112 and determines whether anyunobserved fractures inconsistently intersect any imaged intervals basedon the altered values.

If the method 100 determines at step 112 that the there are nounobserved fractures that inconsistently intersect any of the imagedintervals, the method 100 at step 120, as illustrated in FIG. 1B,locates a triangle of size M (i.e., the minimum size of the fractures tobe simulated) at each seed point having the prescribed orientation. Themethod 100 marks all triangle edges as open for growth at step 122. Atstep 124, the method 100 randomly selects an open edge and adds a newtriangle of size M to the selected open edge. In one embodiment, themethod 100 uses a kriging method to simulate the orientation of the newtriangle using adjacent triangles as conditioning data.

While performing the kriging method, the method 100 checks for one ofthree possible scenarios that may occur. One, if the fracture's strikelength reaches the target strike length (SL) at step 128, the method 100at step 136 marks all horizontal edges as closed to growth. Two, if thedip length reaches the target dip length (DL) at step 132, the method100 at step 138 marks all vertical edges as closed to growth. The thirdscenario is if a triangle touches a different fracture at step 134. Ifthis occurs, in one embodiment, the method 100 uses the probability thata fracture from the current fracture set truncates against anotherfracture set (Prob{T_(ij)}) to decide if the propagating fracture shouldbe truncated. If the method 100 determines that the propagating fractureshould be truncated, the method 100 closes all edges that reach thefracture against which it terminates.

Once the method 100 closes an open edge based on the occurrence of theone of the above scenarios, the method 100 determines whether any openedges remain at step 142, and if so, the method 100 repeats the processat step 124 on a remaining open edge. Once all edges are closed, themethod 100 writes the triangulation to an output file. The method 100may perform additional post processing to add aperture, φ and k at step152.

At step 154, the method 100 determines whether to perform anotherrealization. If additional realizations are needed, the method 100repeats the above process beginning at step 106. If no additionalrealizations are needed, the method 100 terminates.

FIG. 4 is a block diagram illustrating one embodiment of a system 400for implementing the features and functions of the disclosedembodiments. The system 400 includes, among other components, aprocessor 400, main memory 402, secondary storage unit 404, aninput/output interface module 406, and a communication interface module408. The processor 400 may be any type or any number of single core ormulti-core processors capable of executing instructions for performingthe features and functions of the disclosed embodiments.

The input/output interface module 406 enables the system 400 to receiveuser input (e.g., from a keyboard and mouse) and output information toone or more devices such as, but not limited to, printers, external datastorage devices, and audio speakers. The system 400 may optionallyinclude a separate display module 410 to enable information to bedisplayed on an integrated or external display device. For instance, thedisplay module 410 may include instructions or hardware (e.g., agraphics card or chip) for providing enhanced graphics, touchscreen,and/or multi-touch functionalities associated with one or more displaydevices. For example, in one embodiment, the display module 410 is aNVIDIA® QuadroFX type graphics card that enables viewing andmanipulating of three-dimensional objects.

Main memory 402 is volatile memory that stores currently executinginstructions/data or instructions/data that are prefetched forexecution. The secondary storage unit 404 is non-volatile memory forstoring persistent data. The secondary storage unit 404 may be orinclude any type of data storage component such as a hard drive, a flashdrive, or a memory card. In one embodiment, the secondary storage unit404 stores the computer executable code/instructions and other relevantdata for enabling a user to perform the features and functions of thedisclosed embodiments.

For example, in accordance with the disclosed embodiments, the secondarystorage unit 404 may permanently store the executable code/instructionsof an algorithm 420 for providing a geostatistical procedure forconditional simulation of the 3D geometry of a natural fracture networkconditioned by well bore observations as described above. Theinstructions associated with the algorithm 420 are then loaded from thesecondary storage unit 404 to main memory 402 during execution by theprocessor 400 for performing the disclosed embodiments. In addition, thesecondary storage unit 1104 may store other executable code/instructionsand data 422 such as, but not limited to, a reservoir simulationapplication for use with the disclosed embodiments.

The communication interface module 408 enables the system 400 tocommunicate with the communications network 430. For example, thenetwork interface module 408 may include a network interface card and/ora wireless transceiver for enabling the system 400 to send and receivedata through the communications network 430 and/or directly with otherdevices.

The communications network 430 may be any type of network including acombination of one or more of the following networks: a wide areanetwork, a local area network, one or more private networks, theInternet, a telephone network such as the public switched telephonenetwork (PSTN), one or more cellular networks, and wireless datanetworks. The communications network 430 may include a plurality ofnetwork nodes (not depicted) such as routers, network accesspoints/gateways, switches, DNS servers, proxy servers, and other networknodes for assisting in routing of data/communications between devices.

For example, in one embodiment, the system 400 may interact with one ormore servers 434 or databases 432 for performing the features of thepresent invention. For instance, the system 400 may query the database432 for well log information in accordance with the disclosedembodiments. In one embodiment, the database 432 may utilize OpenWorks®software available from Landmark Graphics Corporation to effectivelymanage, access, and analyze a broad range of oilfield project data in asingle database. Further, in certain embodiments, the system 400 may actas a server system for one or more client devices or a peer system forpeer to peer communications or parallel processing with one or moredevices/computing systems (e.g., clusters, grids).

While specific details about the above embodiments have been described,the above hardware and software descriptions are intended merely asexample embodiments and are not intended to limit the structure orimplementation of the disclosed embodiments. For instance, although manyother internal components of the system 400 are not shown, those ofordinary skill in the art will appreciate that such components and theirinterconnection are well known.

In addition, certain aspects of the disclosed embodiments, as outlinedabove, may be embodied in software that is executed using one or moreprocessing units/components. Program aspects of the technology may bethought of as “products” or “articles of manufacture” typically in theform of executable code and/or associated data that is carried on orembodied in a type of machine readable medium. Tangible non-transitory“storage” type media (i.e., a computer program product) include any orall of the memory or other storage for the computers, processors or thelike, or associated modules thereof, such as various semiconductormemories, tape drives, disk drives, optical or magnetic disks, and thelike, which may provide storage at any time for the softwareprogramming.

Additionally, the flowchart and block diagrams in the figures illustratethe architecture, functionality, and operation of possibleimplementations of systems, methods and computer program productsaccording to various embodiments of the present invention. It shouldalso be noted that, in some alternative implementations, the functions,instructions, or code noted in a block diagram or illustrated pseudocodemay occur out of the order noted in the figures. For example, two blocksshown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

Accordingly, the disclosed embodiments provide a system, computerprogram product, and method for providing a geostatistical procedure forconditional simulation of the 3D geometry of a natural fracture networkconditioned by well bore observations. In addition to the embodimentsdescribed above, many examples of specific combinations are within thescope of the disclosure, some of which are detailed below.

One example embodiment is a computer-implemented method for generating asimulation of a three dimensional (3D) geometry of a natural fracturenetwork, the method includes determining parameters for performing thesimulation of the 3D geometry of the natural fracture network;determining locations of seed points for fractures. The method assignsto each seed point a target strike length and target dip length. Themethod also assigns to each seed point an initial strike length and aninitial dip length. The method located a triangle of a minimum size ofthe fractures to be simulated at each seed point and marks all edges ofthe triangle as open for growth. While the triangle has at least oneopen edge, the method selects an open edge of the triangle and adds newtriangles of the minimum size of the fractures to be simulated to theopen edge until one condition of a set of conditions is met.

In one embodiment, the set of conditions comprises a strike length ofthe fracture reaching the target strike length, a dip length of thefracture reaching the target dip length, and the new triangle touching adifferent fracture. In response to the one condition being met, themethod closes at least one open edge of the triangle. For example, inone embodiment, the computer-implemented method closes all horizontaledges of the triangle in response to a determination that the onecondition of the set of conditions that is met is the strike length ofthe fracture reaching the target strike length. In the same embodiment,the method may close all vertical edges of the triangle in response to adetermination that the one condition of the set of conditions that ismet is the dip length of the fracture reaching the target dip length.

In certain embodiments of the above example embodiment, the parametersare determined from data analysis and geological analogs. In someembodiments, the parameters may include one or more of the following: aminimum size of the fractures to be simulated, a number of fracturesets, a cumulative frequency distribution of the strike length for thefractures in each fracture set, a probability distribution of a ratio ofthe strike length to the dip length for the fractures in the fractureset, a probability distribution of a strike angle and a probabilitydistribution of a dip angle for the fractures in the fracture set, adegree of clustering of the fractures in the fracture set, and a degreeof smoothness of the fractures in the fracture set. In some embodiments,the above example computer-implemented method embodiment may furtherinclude determining a probability that a fracture from first settruncates against a fracture from a second set.

Additionally, in some embodiments of the above examplecomputer-implemented method, the parameters are determined from at leastone image log of at least one wellbore. In addition, the abovecomputer-implemented method may include determining a number of observedfractures from the at least one image log of the at least one wellbore.For each observed fracture, the computer-implemented method determines alocation coordinates where an observed fracture intersects a wellboreand also determines the strike length and the dip length of the observedfracture at the intersection of the observed fracture and the wellbore.Still, in certain embodiments, the computer-implemented method mayinclude the steps of determining a number of imaged intervals over whichan image log provides data; and for each image interval, determiningcoordinates of endpoints corresponding to the imaged interval.

As part of the process of determining the locations of seed points forthe fractures, in certain embodiments, the computer-implemented methodstarts from locations of observed fractures and adds probabilisticallyselected locations for additional unobserved fractures until a targetfrequency is reached for a fracture set.

In some embodiments, the computer-implemented method assigns to eachseed point the target strike length and the target dip length byrespectively drawing random values from a cumulative frequencydistribution of the strike length for the fractures in a fracture setand from a probability distribution of a ratio of the strike length tothe dip length for the fractures in the fracture set.

Another embodiment of the above disclosed computer-implemented methodmay include determining whether any unobserved fractures inconsistentlyintersect any imaged intervals; and altering at least one of the targetstrike length, the target dip length, the initial strike length, and theinitial dip length in response to a determination that an unobservedfracture inconsistently intersects an imaged interval.

A second example embodiment based on the above disclosure is a system,comprising: at least one processor; and at least one memory coupled tothe at least one processor and storing computer executable instructionsfor generating a simulation of a three dimensional (3D) geometry of anatural fracture network, the computer executable instructions comprisesinstructions for: determining parameters for performing the simulationof the 3D geometry of the natural fracture network; determininglocations of seed points for fractures; assigning to each seed point atarget strike length and target dip length; assigning to each seed pointan initial strike length and an initial dip length; locating a triangleof a minimum size of the fractures to be simulated at each seed point;marking all edges of the triangle as open for growth; and while thetriangle has at least one open edge, selecting an open edge of thetriangle, repeating a step of adding a new triangle of the minimum sizeof the fractures to be simulated to the open edge until one condition ofa set of conditions is met, the set of conditions comprising a strikelength of the fracture reaching the target strike length, a dip lengthof the fracture reaching the target dip length, and the new triangletouching a different fracture, and closing at least one edge of thetriangle in response to the one condition being met.

Still, another example is a non-transitory computer readable mediumcomprising computer executable instructions for generating a simulationof a three dimensional (3D) geometry of a natural fracture network, thecomputer executable instructions when executed causes one or moremachines to perform operations comprising: determining parameters forperforming the simulation of the 3D geometry of the natural fracturenetwork; determining locations of seed points for fractures; assigningto each seed point a target strike length and target dip length;assigning to each seed point an initial strike length and an initial diplength; locating a triangle of a minimum size of the fractures to besimulated at each seed point; marking all edges of the triangle as openfor growth; and while the triangle has at least one open edge, selectingan open edge of the triangle, repeating a step of adding a new triangleof the minimum size of the fractures to be simulated to the open edgeuntil one condition of a set of conditions is met, the set of conditionscomprising a strike length of the fracture reaching the target strikelength, a dip length of the fracture reaching the target dip length, andthe new triangle touching a different fracture, and closing at least oneedge of the triangle in response to the one condition being met.

The above second and third example embodiments may similarly be modifiedin various embodiments as described above with respect to the firstexample embodiment. However the above specific example embodiments andmodifications are not intended to limit the scope of the claims. Forinstance, the example embodiments may be modified by including,excluding, or combining one or more features or functions described inthe disclosure.

As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise”and/or “comprising,” when used in this specification and/or the claims,specify the presence of stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof. The correspondingstructures, materials, acts, and equivalents of all means or step plusfunction elements in the claims below are intended to include anystructure, material, or act for performing the function in combinationwith other claimed elements as specifically claimed. The description ofthe present invention has been presented for purposes of illustrationand description, but is not intended to be exhaustive or limited to theinvention in the form disclosed. Many modifications and variations willbe apparent to those of ordinary skill in the art without departing fromthe scope and spirit of the invention. The embodiment was chosen anddescribed to explain the principles of the invention and the practicalapplication, and to enable others of ordinary skill in the art tounderstand the invention for various embodiments with variousmodifications as are suited to the particular use contemplated. Thescope of the claims is intended to broadly cover the disclosedembodiments and any such modification.

The invention claimed is:
 1. A computer-implemented method comprising:determining parameters for simulating a three dimensional (3D) geometryof a natural fracture network; determining locations of seed points forfractures to be simulated; assigning to each seed point a target strikelength and target dip length; locating a triangulated fracture of apredetermined size to be simulated at each seed point; marking all edgesof the triangulated fracture as open for growth; while the triangulatedfracture has at least one edge marked open, simulating, by a processor,the 3D geometry of the natural fracture network by: selecting the atleast one edge of the triangulated fracture that is marked open;repeating a step of adding a new triangulated fracture of thepredetermined size to be simulated to the at least one edge marked openuntil at least one of a set of conditions is met, the set of conditionscomprising a strike length of the triangulated fracture reaching thetarget strike length, a dip length of the triangulated fracture reachingthe target dip length, and the new triangulated fracture touching adifferent triangulated fracture within the 3D geometry of the naturalfracture network; and marking the at least one edge of the triangulatedfracture as closed for growth in response to the at least one conditionbeing met; and estimating reserves of a petroleum reservoir based on thesimulation.
 2. The computer-implemented method of claim 1, wherein theparameters are determined from data analysis and geological analogs. 3.The computer-implemented method of claim 2, wherein the parametersinclude a predetermined size of the fractures to be simulated and anumber of fracture sets.
 4. The computer-implemented method of claim 3,further comprising determining a cumulative frequency distribution ofthe strike length for the fractures in each fracture set and aprobability distribution of a ratio of the strike length to the diplength for the fractures in the fracture set.
 5. Thecomputer-implemented method of claim 4, further comprising determining aprobability distribution of a strike angle and a probabilitydistribution of a dip angle for the fractures in the fracture set. 6.The computer-implemented method of claim 5, further comprisingdetermining a degree of clustering and a degree of smoothness of thefractures in the fracture set.
 7. The computer-implemented method ofclaim 6, further comprising determining a probability that a fracturefrom first set truncates against a fracture from a second set.
 8. Thecomputer-implemented method of claim 2, wherein the parameters arefurther determined from at least one image log of at least one wellbore.9. The computer-implemented method of claim 8, further comprising:determining a number of observed fractures from the at least one imagelog of the at least one wellbore; and for each observed fracture,determining a location coordinates where an observed fracture intersectsa wellbore, determining the strike length and the dip length of theobserved fracture at an intersection of the observed fracture and thewellbore.
 10. The computer-implemented method of claim 9, furthercomprising: determining a number of imaged intervals over which an imagelog provides data; and for each image interval, determining coordinatesof endpoints corresponding to the imaged interval.
 11. Thecomputer-implemented method of claim 1, wherein determining thelocations of seed points for the fractures comprises starting fromlocations of observed fractures and adding probabilistically selectedlocations for additional unobserved fractures until a target frequencyis reached for a fracture set.
 12. The computer-implemented method ofclaim 1, wherein assigning to each seed point the target strike lengthand the target dip length is performed by drawing random values from acumulative frequency distribution of the strike length for the fracturesin a fracture set and from a probability distribution of a ratio of thestrike length to the dip length for the fractures in the fracture set.13. The computer-implemented method of claim 1, further comprisingdetermining whether any unobserved fractures inconsistently intersectany imaged intervals; and altering the target strike length and thetarget dip length in response to a determination that an unobservedfracture inconsistently intersects an imaged interval.
 14. Thecomputer-implemented method of claim 1, wherein marking the at least oneedge of the triangulated fracture as closed in response to the onecondition being met comprises marking all horizontal edges of thetriangulated fracture as closed in response to a determination that theone condition of the set of conditions that is met is the strike lengthof the triangulated fracture reaching the target strike length.
 15. Thecomputer-implemented method of claim 1, wherein marking the at least oneedge of the triangulated fracture as closed in response to the onecondition being met comprises marking all vertical edges of thetriangulated fracture as closed in response to a determination that theone condition of the set of conditions that is met is the dip length ofthe triangulated fracture reaching the target dip length.
 16. A system,comprising: at least one processor; and at least one memory coupled tothe at least one processor and storing computer executable instructions,which when executed by the processor cause the processor to perform aplurality of functions, including functions to: determine parameters forsimulating a three dimensional (3D) geometry of a natural fracturenetwork; determine locations of seed points for fractures to besimulated; assign to each seed point a target strike length and targetdip length; locate a triangulated fracture of a predetermined size to besimulated at each seed point; mark all edges of the triangulatedfracture as open for growth; simulate the 3D geometry of the naturalfracture network; and estimate reserves of a petroleum reservoir basedon the simulation, wherein the simulation is performed while thetriangulated fracture has at least one edge marked open, and thefunctions performed by the processor for the simulation includefunctions to: select the at least one edge of the triangulated fracturethat is marked open; add a new triangulated fracture of thepredetermined size to be simulated to the at least one edge marked openuntil at least one of a set of conditions is met, the set of conditionscomprising a strike length of the triangulated fracture reaching thetarget strike length, a dip length of the triangulated fracture reachingthe target dip length, and the new triangulated fracture touching adifferent triangulated fracture within the 3D geometry of the naturalfracture network; and mark the at least one edge of the triangulatedfracture as closed for growth in response to the at least one conditionbeing met.
 17. The system of claim 16, wherein the parameters aredetermined from at least one image log of at least one wellbore, andwherein the computer executable instructions further comprisesinstructions for: determining a number of observed fractures from the atleast one image log of the at least one wellbore; and for each observedfracture, determining a location coordinates where an observed fractureintersects a wellbore, determining the strike length and the dip lengthof the observed fracture at an intersection of the observed fracture andthe wellbore.
 18. The system of claim 17, wherein the computerexecutable instructions further comprises instructions for: determininga number of imaged intervals over which an image log provides data; andfor each image interval, determining coordinates of endpointscorresponding to the imaged interval.
 19. The system of claim 16,wherein the computer executable instructions further comprisesinstructions for determining whether any unobserved fracturesinconsistently intersect any imaged intervals; and altering the targetstrike length, the target dip length, the initial strike length, and theinitial dip length in response to a determination that an unobservedfracture inconsistently intersects an imaged interval.
 20. Anon-transitory computer readable medium comprising computer executableinstructions which when executed causes one or more machines to performoperations comprising: determining parameters simulating a threedimensional (3D) geometry of a natural fracture network; determininglocations of seed points for fractures to be simulated; assigning toeach seed point a target strike length and target dip length; locating atriangulated fracture of a predetermined size to be simulated at eachseed point; marking all edges of the triangulated fracture as open forgrowth; while the triangulated fracture has at least one edge markedopen, simulating the 3D geometry of the natural fracture network by:selecting the at least one edge of the triangulated fracture that ismarked open; repeating a step of adding a new triangulated the fractureof predetermined size to be simulated to the at least one edge markedopen until at least one of a set of conditions is met, the set ofconditions comprising a strike length of the triangulated fracturereaching the target strike length, a dip length of the triangulatedfracture reaching the target dip length, and the new triangulatedfracture touching a different triangulated fracture within the 3Dgeometry of the natural fracture network; and marking the at least oneedge of the triangulated fracture as closed for growth in response tothe at least one condition being met; and estimating reserves of apetroleum reservoir based on the simulation.